In this class, we will explore the technologies that scholars use for humanities and social science research, delving into their history, advantages, and limitations. Additionally, we will examine the main ongoing discussions in the field of digital humanities.
The course is designed for participants with a diverse profile. It aims to provide the necessary skills for creating digital content to support research in political sciences, modern and contemporary history, economics, and textual sciences.
By the end of the course, you will have completed a digital humanities project for your personal portfolio. The project will be based on your research interests and will demonstrate the skills you have acquired. To achieve this, we will dedicate a portion of our weekly meetings to in-class exercitations and project discussions.
The course is designed for participants with a diverse profile. It aims to provide the necessary skills for creating digital content to support research in political sciences, modern and contemporary history, economics, and textual sciences.
By the end of the course, you will have completed a digital humanities project for your personal portfolio. The project will be based on your research interests and will demonstrate the skills you have acquired. To achieve this, we will dedicate a portion of our weekly meetings to in-class exercitations and project discussions.
scheda docente
materiale didattico
- What is Digital Humanities? Can it be defined?
- The history of Digital Humanities.
- What is ‘data’?
- Forms of data and data-sets.
- Data cleaning and manipulation.
- Presenting data. Data analysis.
- Reconsidering data manipulation. Missing data.
- Data visualization: history, methods, and tools.
- Text analysis and topic modeling; possibilities and drawbacks.
- Algorithms of textual analysis.
- Infographic: A history of data graphics.
- Introduction to HTML and CSS.
- Concepts of web design.
- Digital maps.
- GIS and digital gazetteers.
- Introduction to AI: From the first models to machine learning.
- Deep machine learning.
- An introduction to artificial neural networks.
Programma
Please refer to the syllabus on the course's website: https://digitalhumanities.site/syllabus- What is Digital Humanities? Can it be defined?
- The history of Digital Humanities.
- What is ‘data’?
- Forms of data and data-sets.
- Data cleaning and manipulation.
- Presenting data. Data analysis.
- Reconsidering data manipulation. Missing data.
- Data visualization: history, methods, and tools.
- Text analysis and topic modeling; possibilities and drawbacks.
- Algorithms of textual analysis.
- Infographic: A history of data graphics.
- Introduction to HTML and CSS.
- Concepts of web design.
- Digital maps.
- GIS and digital gazetteers.
- Introduction to AI: From the first models to machine learning.
- Deep machine learning.
- An introduction to artificial neural networks.
Testi Adottati
The materials are listed in the syllabus: https://digitalhumanities.site/syllabusModalità Erogazione
The course is structured as a seminar. Each class typically consists of one or more of these elements: - Discussion of essays, articles, and projects that students have read before the lesson. During this phase, we will analyze the provided materials and explore some of the most relevant digital humanities projects in a reverse-engineering fashion. - Lecture. The lecture will primarily focus on the historical and methodological aspects related to the tools that will be used in the upcoming classes. - In-class exercise. Participants start getting familiar with the tools they will use for their final projects.Modalità Frequenza
Regular attendance in class is crucial, considering the course format.Modalità Valutazione
In the final examination, students will present their projects and discuss the topics covered.